The advantages of platform-based imaging has been long-recognized. Long-range imaging has been known from the time that human observers first went aloft in balloons to make sketches of armies below. Long-range imaging has evolved to include aerial surveillance via powered flight through satellite imaging. Close-range platform-based imaging began with the first magnifying optics, and now employs electron microscopes to detect characteristics of submolecular objects. The need to discriminate and map characteristics of a variety of surfaces led to the development of multispectral instruments to gather and classify information. However, multispectral instruments only record a few bands of the electromagnetic spectrum. Thus, they have little ability to identify a wide variety of surface attributes.
These deficiencies gave rise to techniques involving subdividing the ultraviolet, visible and infrared spectra into distinct “bins”, known as Multispectral Imaging (MSI). In MSI, multiple images of a scene or object are created using light from different parts of the spectrum. If the proper wavelengths are selected, multispectral images can be used to detect an item of interest, such as mineral deposits, camouflage, thermal emissions, and hazardous wastes.
A primary goal of using multispectral remote sensing image data is to discriminate, classify, identify, and quantify materials present in the image. Another important application is subpixel surface characteristic detection, allowing identification of surface attributes having sizes smaller than the pixel resolution. Also important is abundance estimation, which allows detection of concentrations of different signature spectra present in pixels. One difficulty in remote sensing image analysis is that a scene pixel can be mixed linearly or nonlinearly by different materials resident in the pixel, where direct application of commonly used image analysis techniques generally do not work well.
Hyperspectral imaging (HSI) is a method in which remotely sensed data is typically collected using an opto-electrical system that measures reflected solar irradiance. Hyperspectral sensors currently collect data in hundreds of narrow, contiguous wavelengths, so that for each pixel in an image, a reflectance spectrum can be derived that is dependent upon the composition and structure of materials present. Many substances have a unique spectral signature that can be used for identification. In the alternative, the reflective properties of characteristics known to be present can be identified, then “learned” by processing software so as to be readily identified. Moreover, the hundreds of channels allow the detection or identification of more than one material in a pixel. This capability is unique to hyperspectral remote sensing.
The difference between multispectral and hyperspectral is the far greater spectral resolution of the latter achieved by splitting the reflected solar irradiance into many more channels. HSI, like MSI, is a passive technique, in that it depends upon the sun or some other independent illumination source. However, in contract to MSI, HSI creates a larger number of images from contiguous, rather than disjoint, regions of the spectrum, typically, with much finer resolution. This increased sampling of the spectrum provides a great increase in information. Many remote sensing tasks which are impractical or impossible with an MSI system can be accomplished with HSI. The wealth of information available from HSI makes it useful in a variety of applications, such as mineral exploration, hazardous waste remediation, habitat mapping, invasive vegetation detection, and ecosystem monitoring, to name but a few.
One example of an airborne hyperspectral imaging system is the ESSI Probe-1 hyperspectral instrument from Earth Search Science, Inc. The Probe-1 hyperspectral remote sensing airborne system records high resolution spectral reflectance from the earth's surface. Probe-1 is a scanning instrument which records 512 cross-track pixels, each covering 128 wavelengths of light in the 400–2,500 nanometer range. Pixel size is typically between 5 and ten meters on a side as determined by the aircraft's altitude above the surface. Higher resolution is possible if the sensor is mounted on a helicopter rather than a fixed-wing aircraft.
Probe-1 images are built up by collecting successive scan lines as the aircraft moves forward. The size of the imagery in the along-track dimension is determined by the length of the flight line. For example, a 20 kilometer line with 5 meter pixels would be 4,000 by 512 pixels, for a total of 2 million pixels covering over 50 square kilometers. A reflectance spectrum covering 128 wavelengths from visible light through the near infrared and short-wavelength infrared can be derived for each pixel. The field of view of the Probe-1 (60 degrees) allows Earth Search to collect date over large areas quickly.
While the advantages of hyperspectral imaging are many, the mechanisms by which such imaging has been accomplished have presented several problems. For example, optics used in known sensors are typically relatively bulky and unwieldy. In long-range hyperspectral sensors, the gimbaled mounting systems require special structure for mounting and operation. The Probe-1 instrument, while effective, occupies a relatively large amount of cabin space. Known optics require a combination of low altitude, slow airspeed, and degree of stability difficult to obtain using standard aircraft. Similarly, close-range platform-based systems are often difficult to operate in desired applications, such as those requiring close proximity to a living human subject.
Nanotechnology, also known as molecular nanotechnolgy, allows for control of the material world at the nanoscale by taking advantage of quantum-level properties. Nanotechnology provides the means by which systems and materials can be built with exacting specifications and characteristics. The composition and structural modification of existing materials on the nanometer scale can drastically enhance some properties and lead to unprecedented physical effects. In the case of simple materials, structural modification on the nanometer scale may yield an entirely new class materials, whose chemical and physical properties are significantly different from those of the bulk material. This is the bottom-up approach to the manipulation of materials on the nanometer scale and then their assembly into larger scale structures.
Micro-Electro-Mechanical Systems (MEMS) technology is a related and interwoven field of nanotechnology. MEMS technology enables the integration of mechanical, electrical, chemical, thermal, fluidic, magnetic, and optical components on a microscopic scale. MEMS contain elements which allow for the interconversion of energy between these different domains using fabrication techniques leveraged off microelectronics. MEMS devices operate on a sub-conventional scale: minimum feature sizes for micromachining processes often measure under a tenth of a micron. Forces generated by microactuators range from piconewtons to millinewtons, and the displacement of microstructures can be measured to less than a picometer. The incorporation of nanotechnology-modified components and MEMS into a hyperspectral imaging sensor like the Probe-1 can solve the present issues in the field.
In light of the foregoing, there is a need for a MEMS or nanotechnology-modified simple, platform-based remote sensing system capable of overcoming or deducing the drawbacks of known systems, which to be utilized for the imaging and mapping of surface characteristics. The present invention provides such a device.